def test_keepdims(self):
mat = np.eye(3)
for axis in [None, 0, 1]:
tgt = np.percentile(mat, 70, axis=axis, out=None,
overwrite_input=False)
res = np.nanpercentile(mat, 70, axis=axis, out=None,
overwrite_input=False)
assert_(res.ndim == tgt.ndim)
d = np.ones((3, 5, 7, 11))
# Randomly set some elements to NaN:
w = np.random.random((4, 200)) * np.array(d.shape)[:, None]
w = w.astype(np.intp)
d[tuple(w)] = np.nan
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always', RuntimeWarning)
res = np.nanpercentile(d, 90, axis=None, keepdims=True)
assert_equal(res.shape, (1, 1, 1, 1))
res = np.nanpercentile(d, 90, axis=(0, 1), keepdims=True)
assert_equal(res.shape, (1, 1, 7, 11))
res = np.nanpercentile(d, 90, axis=(0, 3), keepdims=True)
assert_equal(res.shape, (1, 5, 7, 1))
res = np.nanpercentile(d, 90, axis=(1,), keepdims=True)
assert_equal(res.shape, (3, 1, 7, 11))
res = np.nanpercentile(d, 90, axis=(0, 1, 2, 3), keepdims=True)
assert_equal(res.shape, (1, 1, 1, 1))
res = np.nanpercentile(d, 90, axis=(0, 1, 3), keepdims=True)
assert_equal(res.shape, (1, 1, 7, 1))
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